Customer data management and business processing method and device, equipment and medium

Abstract

The invention relates to the technical field of financial science and technology, and discloses a customer data management and business processing method, device, equipment and medium, and the method comprises the steps: encrypting and storing obtained target customer data into a data warehouse of a cloud computing platform, and carrying out the access authority control based on a preset authority distribution strategy; performing group portraying on the target customer based on the target customer data, and marking a corresponding label according to a portraying result; when a business handling request is received, identifying a business type; according to the service type and the client label, the priority of the service handling request, service processing personnel and a service processing flow are set in combination with a preset service processing configuration table; and issuing a business handling request to business processing personnel, and allocating temporary authority. According to the invention, through secure storage, accurate portraying and intelligent business distribution of customer data, data security and business processing efficiency are improved, and individuation and accuracy of customer service are realized.

Description

Technical Field

[0001] This invention relates to the fields of customer data management and processing technology and financial technology technology, and in particular to a customer data management and business processing method, apparatus, equipment and medium. Background Technology

[0002] With the rapid development of information technology, customer data management and business processing are playing an increasingly important role in the financial and insurance industry. Especially in the life insurance sector, effective customer data management and business processing not only improve service quality but also enhance customer satisfaction and loyalty. Currently, customer data management and business processing in the financial and insurance industry mainly rely on traditional database management models and manual processing workflows. Business data from different business lines is stored in different business systems and managed separately.

[0003] The inventors recognized that existing customer data management and business processing methods have significant limitations for the insurance industry:

[0004] Firstly, customer business data is too scattered. For example, business data such as insurance applications, complaints, and claims are stored separately in their own business systems, lacking unified management and making it difficult to analyze customer service through comprehensive business data.

[0005] Secondly, existing data management methods do not adequately protect data privacy, allowing business personnel to freely download and view various data, which can easily lead to the leakage of customer data.

[0006] Thirdly, most existing business processes adopt a unified workflow, which fails to be combined with the actual situation of customers, making it difficult to provide customers with more intelligent services, and may even cause customer dissatisfaction and further complaints. Summary of the Invention

[0007] This invention provides a customer data management and business processing method, apparatus, computer equipment, and medium to solve the technical problems of improper management of customer data and overly rigid business processes in the existing insurance industry.

[0008] Firstly, a customer data management and business processing method is provided, including:

[0009] The acquired target customer data is encrypted and stored in a data warehouse built on a cloud computing platform, and access control for the target customer data is implemented based on a preset permission allocation policy. The target customer data includes personal information data, historical business data, and real-time business data.

[0010] Create a group profile of the target customers based on the target customer data, and assign corresponding tags to the target customers based on the profile results;

[0011] Upon receiving a business processing request from a target customer, identify the business type of the request;

[0012] Based on the business type and target customer tags, and combined with the preset business processing configuration table, set the priority of business processing requests, business processing personnel, and business processing flow.

[0013] Issue a business processing request to the business processing personnel and assign them temporary permissions to process the request.

[0014] Secondly, a customer data management and business processing device is provided, including:

[0015] The data storage and access control module is used to encrypt and store the acquired target customer data in a data warehouse built on a cloud computing platform, and to control access permissions to the target customer data based on a preset access control policy. The target customer data includes personal information data, historical business data and real-time business data.

[0016] The tagging module is used to create a group profile of target customers based on target customer data, and to assign corresponding tags to target customers based on the profile results;

[0017] The identification module is used to identify the type of business request when a business processing request is received from a target customer.

[0018] The configuration module is used to set the priority of business processing requests, the personnel handling the business, and the business processing flow based on the business type and the tags of the target customers, combined with the preset business processing configuration table.

[0019] The distribution module is used to distribute business processing requests to business processing personnel and assign temporary permissions to them to process these requests.

[0020] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described customer data management and business processing methods.

[0021] Fourthly, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the steps of the aforementioned customer data management and business processing methods.

[0022] The aforementioned solutions for customer data management and business processing methods, devices, computer equipment, and storage media can leverage cloud computing architecture to establish a unified data platform. This platform integrates business data such as consumer complaints, claims, and information disclosure, enabling centralized data management and rapid analysis. Employing data encryption and data anonymization technologies ensures the security of consumer data during transmission and processing, effectively reducing the risk of data leakage and meeting increasingly stringent privacy protection requirements. Furthermore, by designing dynamic processing flows and integrating machine learning algorithms for in-depth analysis of consumer behavior data, customer profiling is achieved. Flexible adjustments to priorities and processing steps are made using configuration tables and profiling results, providing personalized and precise business services to customers, ensuring efficient business processing, and improving customer satisfaction. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of an application environment for a customer data management and business processing method according to an embodiment of the present invention;

[0025] Figure 2 This is a flowchart illustrating a customer data management and business processing method according to an embodiment of the present invention;

[0026] Figure 3 This is a schematic diagram of a customer data management and business processing device according to an embodiment of the present invention;

[0027] Figure 4 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] The customer data management and business processing methods provided in this invention can be applied to, for example... Figure 1In this application environment, the client is used for customers to input personal data and business requests, as well as to display product recommendations and business processing results. The client communicates with the server via a network, specifically employing end-to-end encryption technology to ensure the security of customer data during transmission. The client transmits customer data to the server via the network, and the server encrypts and stores the acquired target customer data in a data warehouse built on a cloud computing platform. Access control for the target customer data is implemented based on a preset permission allocation policy. The target customer data includes personal information, historical business data, and real-time business data. Then, the server creates a group profile of the target customers based on the target customer data and tags them accordingly. When the server receives a business processing request from a target customer through the client, it identifies the business type of the request. Based on the business type and the target customer's tags, and combined with a preset business processing configuration table, the server sets the priority, personnel, and processing flow of the business processing request. The server then issues the business processing request to the personnel and assigns them temporary permissions to process the request. The client can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server-side implementation uses a cloud computing platform. The invention will now be described in detail through specific embodiments.

[0030] Please see Figure 2 As shown, Figure 2 A flowchart illustrating a customer data management and business processing method provided in an embodiment of the present invention includes the following steps:

[0031] Step S1: Encrypt and store the acquired target customer data in a data warehouse built on a cloud computing platform, and control access permissions to the target customer data based on a preset permission allocation policy. The target customer data includes personal information data, historical business data, and real-time business data.

[0032] The target customer data includes personal information data, historical business data, and real-time business data. Personal information data is entered by the customer during initial registration and uploaded to the cloud computing platform for storage. Historical business data is obtained based on the customer's past transactions. Real-time business data represents the customer's currently active transactions. It should be noted that this business data includes, but is not limited to, insurance application data, claims data, and complaint data; all business data generated by insurance or other value-added services (such as health management services) is included.

[0033] To enhance customer data privacy, customer data is encrypted during the data storage process, thereby reducing the possibility of data leakage. Furthermore, after customer data is stored, access control is implemented through preset permission allocation policies to prevent unauthorized access and further reduce the likelihood of data leakage.

[0034] In this embodiment, target customer data is uniformly integrated and stored in the data warehouse of the cloud computing platform. This facilitates unified management of customer data and enables a more comprehensive analysis of customer business needs, allowing for personalized services. Furthermore, the cloud computing platform offers high scalability and availability. Utilizing the elastic resources of cloud computing, it enables real-time processing and analysis of large-scale data, meeting peak business demands. Multi-regional redundant deployment ensures system stability and reliability, preventing processing delays due to system failures.

[0035] Furthermore, in step S1, the step of encrypting and storing the acquired target customer data in a data warehouse built on a cloud computing platform specifically includes:

[0036] 1.1 When target customer data is obtained, the target customer data is classified according to preset rules, and each category of data is encrypted using a preset encryption strategy and key.

[0037] To prevent customer data leakage, this embodiment employs international standard encryption algorithms such as AES-256 (Advanced Encryption Standard) and RSA-2048, combined with a key management mechanism, to ensure data security during transmission and storage. Before data transmission, the data is compressed and then encrypted to reduce data transmission volume and improve encryption efficiency. Simultaneously, a data classification encryption mechanism is introduced. Specifically, this embodiment categorizes customer data according to its sensitivity and purpose. For example, based on users, customer data can be divided into categories such as identity information, health information, and claims records. Based on sensitivity, customer data can be divided into highly sensitive information (such as health information and identity information in life insurance), moderately sensitive information (such as insured amount information and claims record information), and low-sensitivity information (such as insurance application time information and insurance type information). Different encryption strategies and keys are assigned to each type of data. For example, homomorphic encryption technology is used for health information to ensure that the data can still be calculated and analyzed even in an encrypted state.

[0038] 1.2 Transmit the encrypted target customer data to the cloud computing platform and store it in the data warehouse.

[0039] This embodiment categorizes and encrypts customer data, requiring each category to be decrypted before all information is leaked, thus preventing large-scale data breaches and further reducing the risks associated with customer data leaks.

[0040] Furthermore, in order to provide customers with better services, after step S1, which involves encrypting and storing the acquired target customer data in a data warehouse built on a cloud computing platform, the method further includes:

[0041] 1.3 Utilize cloud computing platforms to analyze and predict target customer data in real time, and generate prediction results, including at least one of insurance purchase prediction, complaint prediction, claims prediction, and visit behavior prediction.

[0042] Specifically, this embodiment utilizes the real-time computing capabilities of a cloud computing platform to perform real-time analysis of target customer data and predict the target customer's business needs. For example, it monitors consumer complaint behavior in real time to predict potential high-risk complaints; it analyzes consumer claim applications in real time to predict claim amounts and processing times. Through the analysis and prediction of target customer data, prediction results are obtained, such as predicting the types of complaints a customer might raise; and predicting a customer's claim needs and the range of amounts.

[0043] 1.4. Generate personalized suggestions based on the prediction results and push them to target customers through multiple channels.

[0044] Specifically, after predicting customers' business needs, corresponding personalized suggestions are developed based on the prediction results and pushed to customers through multiple channels (such as SMS, email, and app push notifications). For example: suggestions regarding complaints: such as providing priority processing channels for high-risk complainants, or proactively contacting consumers to understand their specific needs; suggestions regarding claims: such as providing a faster claims process for consumers with high claims needs, or recommending suitable claims solutions; suggestions regarding insurance: such as recommending suitable insurance types for consumers with low insurance needs, or offering insurance discounts; suggestions regarding behavior: such as providing personalized reminder services for consumers with low access frequency, or pushing relevant product information.

[0045] 1.5. Monitor feedback from target customers in real time.

[0046] Specifically, in order to ensure timely follow-up on customer needs, after pushing personalized suggestions to customers, we monitor customer feedback in real time. For example, we can determine whether a customer is interested in a suggestion by statistically analyzing the time and frequency of a customer's viewing of a certain recommendation on the APP, and push more detailed information or services to the customer after confirming that the customer is interested.

[0047] Furthermore, in step S1, the step of controlling access permissions to target customer data based on a preset permission allocation strategy specifically includes:

[0048] 2.1. Based on the characteristics of the insurance industry, conduct a sensitivity assessment on the target customer data, and classify the target customer data into high-sensitivity data, medium-sensitivity data, and low-sensitivity data according to the sensitivity assessment results.

[0049] Specifically, after acquiring target customer data, the sensitivity levels of this data can be categorized according to the business characteristics of the insurance industry across different business scenarios. For example, for life insurance, business scenarios can be divided into policy information inquiry, claims record viewing, complaint handling, data analysis and report generation, etc. High-sensitivity data can include health information and identity information, medium-sensitivity data can include insured amount and claims records, and low-sensitivity data can include policy purchase time and insurance type. For auto insurance, high-sensitivity data can include vehicle annual inspection data, vehicle maintenance records, and vehicle owner identity information, medium-sensitivity data can include auto insurance amount and auto insurance claims records, and low-sensitivity data can include auto insurance purchase time and auto insurance type.

[0050] 2.2 Based on the preset privacy policy configuration table, access rules for highly sensitive data, medium sensitive data, and low sensitive data are set according to business scenarios. Business scenarios are pre-divided based on business needs.

[0051] Specifically, after classifying customer data according to sensitivity, access rules are set for each sensitivity level to restrict access permissions for different users. For example, highly sensitive data is only accessible to authorized personnel, medium-sensitive data is subject to access control based on user roles and task requirements, and low-sensitive data can be accessed relatively freely, but basic authentication is still required.

[0052] 2.3. Grant access permissions to users in accordance with access rules.

[0053] In this embodiment, customer data is divided into three levels—highly sensitive, moderately sensitive, and lowly sensitive—based on the importance of data in different business scenarios. Access rules are then set for each level of data to achieve access control over customer data, prevent arbitrary access to customer data, and reduce the risk of customer data leakage.

[0054] Furthermore, after granting access rights to users according to the access rules, the process also includes:

[0055] 2.4 Real-time monitoring of visitor behavior and changes in business needs.

[0056] 2.5 Adjust access permissions for users when access behavior triggers warning conditions or business needs change.

[0057] Specifically, when personnel access target customer data, their access behavior is monitored in real time. This behavior includes, but is not limited to, the frequency and duration of access to sensitive data at various levels, the time of access (e.g., during working hours or non-working hours), and whether access to customer data exceeds business needs (e.g., accessing data related to complaints when processing claims). These business needs changes include user role changes and data classification adjustments. When a personnel's access behavior triggers an alert, their access permissions can be automatically revoked. For example, when access to unauthorized highly sensitive data is detected, their access permissions are automatically revoked; when triggers requiring permission adjustments are detected (e.g., user role changes, data classification adjustments), the permission adjustment process is immediately initiated, revoking the personnel's current access permissions and re-authorizing them.

[0058] This embodiment monitors the access behavior of visitors and changes in business needs. When visitors engage in inappropriate access behavior, their access permissions are restricted to prevent data leakage. When business needs change, the access permissions of visitors are adjusted in a timely manner to avoid affecting their normal access needs.

[0059] Furthermore, following the step of real-time monitoring of visitors' access behavior, the following steps are also included:

[0060] 2.6. De-identify the target customer data accessed by the visitors based on their current business scenario.

[0061] To prevent data leakage without affecting data usage, this embodiment performs data anonymization processing based on the data type when accessing target customer data, thus preventing data information leakage. For example, based on the characteristics of the life insurance industry, sensitive customer data is divided into different categories, such as: identity information, including name, ID number, contact information, etc.; health information, including health status, medical history, physical examination reports, etc.; and financial information, including insured amount, claims records, payment information, etc. Then, a sensitivity assessment is performed on each type of data to determine its protection level during processing. For example, health information and identity information are usually considered highly sensitive data and require strict anonymization processing. During the data anonymization process, appropriate anonymization methods can be selected according to the data type and purpose, such as: replacement method: replacing sensitive fields, such as replacing ID numbers with randomly generated strings; masking method: masking some characters in sensitive fields, such as replacing the middle few digits of a mobile phone number with asterisks; encryption method: encrypting sensitive data to ensure data security during transmission and storage; and randomization method: randomizing sensitive data to remove its original meaning while still maintaining the statistical characteristics of the data. In this embodiment, homomorphic encryption technology can also be used for customer data to ensure that the data can still be calculated and analyzed in an anonymized state, thereby supporting subsequent business processing and data analysis.

[0062] Furthermore, in some embodiments, dynamic desensitization rules can be set to dynamically desensitize data according to data classification, business scenarios, and data processing needs. For example, in the process of handling complaints, it may be necessary to desensitize the customer's name information in real time to protect privacy, while in the process of claims, it is not necessary to desensitize the customer's name information.

[0063] Step S2: Create a group profile of the target customers based on the target customer data, and assign corresponding tags to the target customers according to the profile results.

[0064] Specifically, the target customer data comprises customers' personal information, historical business data, and real-time business data. This comprehensive and rich data fully reflects customers' business needs, behavioral characteristics, personality traits, and preferences. Therefore, this embodiment uses the target customer data to create a profile of the target customers, and then tags the target customers based on this profile. For example, the profile can be used to label target customers as "high-risk customers," "young and middle-aged customers," or "high-net-worth customers," or as business tags such as "insurance needs," "claims needs," or "complaint needs."

[0065] Furthermore, step S2 specifically includes:

[0066] 1. Extract key feature information from target customer data.

[0067] Specifically, key characteristic information can be extracted from target customer data, including demographic characteristics (age, gender, occupation, income, etc.), behavioral characteristics (insurance habits, claim frequency, service consultation methods, etc.), preference characteristics (product preferences, service channel preferences, etc.), and social network characteristics (family structure, social relationships, etc.).

[0068] 2. Input key feature information into a pre-built analysis model for analysis and prediction to obtain profile results. The analysis model includes at least one of cluster analysis model, demand prediction model, association rule mining model, and time series analysis model. The profile results include at least one of customer group segmentation information, customer business demand prediction information, customer behavior correlation information, and customer behavior trend information over time series.

[0069] It should be noted that this analytical and predictive model includes at least one of the following: clustering analysis model, demand forecasting model, association rule mining model, and time series analysis model. Specifically, the clustering analysis model, built on clustering algorithms, is used to segment customers into different groups (such as high-risk customers, young and middle-aged customers, high-net-worth customers, etc.); the demand forecasting model, built using classification algorithms, is used to predict possible types of customer complaints and claims needs; the association rule mining model, built using pre-set association rules, is used to discover relationships between customer behaviors (such as customers who have purchased a certain type of insurance are more likely to file claims); and the time series analysis model, built based on the results of time series analysis of customer behavior, is used to analyze the temporal trends of customer behavior (such as the seasonal variation in complaint volume).

[0070] 3. Tag the target customers according to the profile results. The tags include at least one of the following: customer group type, customer business demand prediction results, behavioral correlation between customers, and customer behavior analysis results.

[0071] In this embodiment, customer group profiles are created by utilizing integrated target customer data. These profiles can provide accurate information for subsequent business services, such as designing personalized business processes or product recommendations for different groups, thereby minimizing customer complaints during the business process and providing a good customer experience.

[0072] Step S3: When a business processing request is received from a target customer, identify the business type of the business processing request.

[0073] Specifically, when the system receives a business processing request submitted by a target customer through online platforms, customer service hotlines, business outlets, etc., it identifies the business type of the business processing request through natural language processing and business rule engine. The business types include insurance business, policy change business, claims business, consultation and complaint business, etc.

[0074] Step S4: Based on the business type and target customer tags, and in conjunction with the preset business processing configuration table, set the priority of business processing requests, the business processing personnel, and the business processing flow.

[0075] In this embodiment, a pre-configured business processing configuration table is set up, which records the priority of various businesses, the permission level of the processing personnel, and the pre-set business processing flow under different business scenarios.

[0076] Specifically, the system queries a pre-defined business processing configuration table based on the business type and target customer tags to determine the priority of business processing requests. For example, a request tagged "high-risk customer" and with a business type of "complaint business" is set to the highest priority and assigned to a processing personnel with advanced permissions, with an additional evaluation step added to the business processing flow to ensure the comprehensiveness and accuracy of the processing; a request tagged "family customer" and with a business type of "policy change business" is set to medium priority and assigned to a processing personnel with ordinary permissions, without requiring additional business processing steps.

[0077] Step S5: Issue a business processing request to the business processing personnel and assign them temporary permissions to process the business processing request.

[0078] Specifically, the priority of business processing requests, the personnel handling the business, and the business processing flow are set. The business processing requests are then sent to the corresponding personnel for processing, and the corresponding permissions are assigned to the personnel to ensure that the personnel can process the business processing requests in a timely and accurate manner.

[0079] Furthermore, during the business process, the business progress can be monitored in real time and feedback can be sent to the target customers in real time, so that the target customers can understand the business progress in a timely manner.

[0080] This embodiment's customer data management and business processing method introduces a cloud computing architecture to establish a unified data platform. This platform integrates business data such as consumer complaints, claims, and information disclosure, enabling centralized data management and rapid analysis. Data encryption and data anonymization technologies are employed to ensure the security of consumer data during transmission and processing, effectively reducing the risk of data leakage and meeting increasingly stringent privacy protection requirements. By designing a dynamic processing flow and integrating machine learning algorithms for in-depth analysis of consumer behavior data, customer profiling is created. Configuration tables and profiling results allow for flexible adjustments to priorities and processing steps, providing personalized and precise business services to customers. This ensures efficient business processing and improves customer satisfaction.

[0081] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0082] In one embodiment, a customer data management and business processing apparatus is provided, which corresponds one-to-one with the customer data management and business processing methods described in the above embodiments. For example... Figure 3 As shown, the customer data management and business processing device includes a data storage and access control module 10, a tag module 11, an identification module 12, a setting module 13, and a distribution module 14.

[0083] The data storage and access control module 10 is used to encrypt and store the acquired target customer data in a data warehouse built on a cloud computing platform, and to control access permissions to the target customer data based on a preset access control policy. The target customer data includes personal information data, historical business data and real-time business data.

[0084] The tag module 11 is used to create a group profile of the target customers based on the target customer data, and to tag the target customers with corresponding tags according to the profile results;

[0085] The identification module 12 is used to identify the business type of the business processing request when it receives a business processing request from a target customer.

[0086] The setting module 13 is used to set the priority of business processing requests, business processing personnel and business processing flow based on business type and target customer tags, combined with the preset business processing configuration table;

[0087] The distribution module 14 is used to distribute business processing requests to business processing personnel and assign temporary permissions to business processing personnel to process business processing requests.

[0088] Optionally, the data storage and access control module 10 performs the operation of encrypting and storing the acquired target customer data in a data warehouse built on a cloud computing platform. Specifically, this includes: when acquiring target customer data, classifying the target customer data according to preset rules, and encrypting the data of each category using preset encryption strategies and keys; transmitting the encrypted target customer data to the cloud computing platform and storing it in the data warehouse.

[0089] Optionally, the data storage and access control module 10 performs access control operations on target customer data based on a preset access allocation strategy. Specifically, this includes: conducting a sensitivity assessment of the target customer data based on the characteristics of the insurance industry, and classifying the target customer data into high-sensitivity data, medium-sensitivity data, and low-sensitivity data according to the sensitivity assessment results; setting access rules for high-sensitivity data, medium-sensitivity data, and low-sensitivity data according to a preset privacy policy configuration table and business scenarios, with business scenarios pre-defined based on business needs; and granting access permissions to users according to the access rules.

[0090] Optionally, after the data storage and access control module 10 performs the operation of granting access permissions to users according to access rules, it is also used to: monitor the access behavior of users and changes in business needs in real time; and adjust the access permissions of users when access behavior triggers warning conditions or when business needs change.

[0091] Optionally, after the data storage and access control module 10 performs the operation of real-time monitoring of the access behavior of the user, it is also used to: de-identify the target customer data accessed by the user according to the user's current business scenario.

[0092] Optionally, the tagging module 11 performs the operation of creating a group profile of the target customers based on the target customer data, and tagging the target customers with corresponding labels according to the profile results. Specifically, this includes: extracting key feature information from the target customer data; inputting the key feature information into a pre-built analysis model for analysis and prediction to obtain the profile results. The analysis model includes at least one of a clustering analysis model, a demand prediction model, an association rule mining model, and a time series analysis model. The profile results include at least one of customer group segmentation information, customer business demand prediction information, customer behavior correlation information, and customer behavior trend information over time. The tags are assigned to the target customers according to the profile results. The tags include at least one of customer group type, customer business demand prediction results, customer behavior correlation, and customer behavior analysis results.

[0093] Optionally, after the data storage and access control module 10 performs the operation of encrypting and storing the acquired target customer data in a data warehouse built on a cloud computing platform, it is also used to: use the cloud computing platform to analyze and predict the target customer data in real time, generate prediction results, including at least one of insurance prediction, complaint prediction, claim prediction, and access behavior prediction; generate personalized suggestions based on the prediction results and push them to the target customer through multiple channels; and monitor the feedback information of the target customer in real time.

[0094] Specific limitations regarding the customer data management and business processing devices can be found in the limitations of the intelligent question-answering method described above, and will not be repeated here. Each module in the aforementioned customer data management and business processing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0095] In one embodiment, a computer device is provided, the internal structure of which can be shown in the following diagram. Figure 4 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it performs the following steps:

[0096] The acquired target customer data is encrypted and stored in a data warehouse built on a cloud computing platform, and access control for the target customer data is implemented based on a preset permission allocation policy. The target customer data includes personal information data, historical business data, and real-time business data.

[0097] Create a group profile of the target customers based on the target customer data, and assign corresponding tags to the target customers based on the profile results;

[0098] Upon receiving a business processing request from a target customer, identify the business type of the request;

[0099] Based on the business type and target customer tags, and combined with the preset business processing configuration table, set the priority of business processing requests, business processing personnel, and business processing flow.

[0100] Issue a business processing request to the business processing personnel and assign them temporary permissions to process the request.

[0101] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0102] The acquired target customer data is encrypted and stored in a data warehouse built on a cloud computing platform, and access control for the target customer data is implemented based on a preset permission allocation policy. The target customer data includes personal information data, historical business data, and real-time business data.

[0103] Create a group profile of the target customers based on the target customer data, and assign corresponding tags to the target customers based on the profile results;

[0104] Upon receiving a business processing request from a target customer, identify the business type of the request;

[0105] Based on the business type and target customer tags, and combined with the preset business processing configuration table, set the priority of business processing requests, business processing personnel, and business processing flow.

[0106] Issue a business processing request to the business processing personnel and assign them temporary permissions to process the request.

[0107] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0108] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0109] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0110] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A customer data management and business processing method, characterized in that, include: The acquired target customer data is encrypted and stored in a data warehouse built on a cloud computing platform, and access control is performed on the target customer data based on a preset permission allocation policy. The target customer data includes personal information data, historical business data, and real-time business data. Based on the target customer data, a group profile is created for the target customers, and corresponding tags are assigned to the target customers according to the profile results; Upon receiving a business processing request from the target customer, the business type of the business processing request is identified; Based on the business type and the target customer's tags, and in conjunction with a preset business processing configuration table, the priority, personnel, and process of the business processing request are set. The business processing request is sent to the business processing personnel, and temporary permissions to process the business processing request are assigned to the business processing personnel.

2. The customer data management and business processing method according to claim 1, characterized in that, The step of encrypting and storing the acquired target customer data in a data warehouse built on a cloud computing platform includes: When target customer data is acquired, it is classified according to preset rules, and each category of data is encrypted using a preset encryption strategy and key. The encrypted target customer data is transmitted to the cloud computing platform and stored in the data warehouse.

3. The customer data management and business processing method according to claim 1, characterized in that, The access control of the target customer data based on the preset permission allocation strategy includes: Based on the characteristics of the insurance industry, the target customer data is subjected to sensitivity assessment, and the target customer data is classified into high-sensitivity data, medium-sensitivity data and low-sensitivity data according to the sensitivity assessment results. Based on a preset privacy policy configuration table, access rules for the highly sensitive data, the moderately sensitive data, and the lowly sensitive data are set according to the business scenarios, and the business scenarios are pre-divided based on business needs; Access permissions are granted to users in accordance with the access rules.

4. The customer data management and business processing method according to claim 3, characterized in that, After granting access permissions to users according to the access rules, the process also includes: Real-time monitoring of the access behavior and changes in business needs of the visitors; When the access behavior triggers an alert or when the business requirements change, the access permissions of the accessing personnel will be adjusted.

5. The customer data management and business processing method according to claim 4, characterized in that, After real-time monitoring of the access behavior of the visitors, the method further includes: The target customer data accessed by the visitor is anonymized based on the visitor's current business scenario.

6. The customer data management and business processing method according to claim 1, characterized in that, The step of creating a group profile of the target customers based on the target customer data and assigning corresponding tags to the target customers according to the profile results includes: Extract key feature information from the target customer data; The key feature information is input into a pre-built analysis model for analysis and prediction to obtain a profile result. The analysis model includes at least one of a clustering analysis model, a demand prediction model, an association rule mining model, and a time series analysis model. The profile result includes at least one of customer group segmentation information, customer business demand prediction information, customer behavior correlation information, and customer behavior trend information over time series. Based on the profile results, the target customers are tagged accordingly. The tags include at least one of the following: customer group type, customer business demand prediction results, behavioral correlation between customers, and customer behavior analysis results.

7. The customer data management and business processing method according to claim 1, characterized in that, After encrypting and storing the acquired target customer data in a data warehouse built on a cloud computing platform, the process also includes: The cloud computing platform is used to analyze and predict the target customer data in real time, and generate prediction results, which include at least one of insurance prediction, complaint prediction, claim prediction, and access behavior prediction. Personalized recommendations are generated based on the prediction results and pushed to the target customers through multiple channels; Real-time monitoring of feedback from the target customers.

8. A customer data management and business processing device, characterized in that, include: The data storage and access control module is used to encrypt and store the acquired target customer data in a data warehouse built on a cloud computing platform, and to control access permissions to the target customer data based on a preset access control policy. The target customer data includes personal information data, historical business data and real-time business data. The tagging module is used to create a group profile of the target customers based on the target customer data, and to tag the target customers with corresponding tags according to the profile results; The identification module is used to identify the business type of the business processing request when it receives the business processing request from the target customer. The setting module is used to set the priority, personnel, and process of the business processing request based on the business type and the target customer's tag, combined with a preset business processing configuration table. The distribution module is used to distribute the business processing request to the business processing personnel and assign temporary permissions to the business processing personnel to process the business processing request.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the customer data management and business processing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the customer data management and business processing method as described in any one of claims 1 to 7.

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